Thales mines ‘data lake’ treasure for Hong Kong mass transit

Making big data speak is unlocking treasure for mass transit operators and commuters through Thales’s pioneering Big Data Analytics platform.

The operator of Hong Kong’s 11 railway lines and 93 stations entrusts Thales with decoding its ‘data lake’ of 10 million inputs created each day by its 5 million passengers as they check in and check out of their journeys.

Putting Big Data to work for transport operators and passengers

Thales transforms passenger information into an asset by making sense of the data.
Its big data analytics platform measures the number of passengers per train, per platform and per station, every 15  minutes or less.  
With an accuracy level of 95 per cent, the journey of each passenger is reconstructed anonymously to enable the computation of key transit performance indicators with the objective to mitigate train and platform crowding, waiting time, or missed trains.
The direct added value for the MTR and its traveling customers of this passenger-centric approach: an ability to improve operations today and to design even more efficient and comfortable commuter experiences tomorrow.
Train occupancy and platform crowding analytics for MTR brings us a lot of useful train service information, which supports us in performance monitoring and service planning for our expanding network.
Stephen Lau, Manager for Market Analysis and Planning at MTR
 By providing an operator with these key performance indicators, it can study, plan and adapt the capacity of the lines and train services, virtually, or by launching pilot projects. This ultimately gives riders a better commuting experience and optimizes network revenue through more efficient operations and the creation of new revenue streams.
Ludovic Lang, Head of Innovation for Thales in Hong Kong.

Simplifying the complex to empower the transport of tomorrow

Thales’s ability to make massive data speak loud and clear is based not only on its significant investments in Big Data Analytics, but also in Connectivity, Artificial Intelligence and Cybersecurity. 
Ludovic Lang comments, “Thales does more than data mining. We do data analytics, predictive analytics through the use of machine learning. All are needed to transform big data into a continuing, valuable asset”.
“In rail, as well as in other types of transport, this added value is a key to operational efficiency, safety, and performance for improved passenger experience” he notes, “Operators in other transport sectors as well are all looking for ways to ‘monetize’ their data to make it a value-added resource each day, and Thales is ready to be their partner to drive their network efficiency and improve the passenger experience”.